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Using Design and Systems Thinking (DST) In Flesh and Blood

This article was written initially for a military audience to describe how design and systems thinking can be helpful for military planners—specifically combating the notion that design cannot produce actionable information. The example I provide illustrates how design can be used for almost anything, and it is not this lofty, squishy, non-decisive process that people associate it with. Design skills can be practiced inside and outside work to grow your ability to unite the design trinity of decision-making, sensemaking, and forecasting. I use Jamshid Gharajedghi’s iterative process to understand the complexity[1] and Philip Tetlock and Dan Gardner’s superforecsting methods[2] in the card game Flesh and Blood. This article was written before the pro tour season to use these models to put myself in the best position of advantage to win a pro tour qualification. The situation leads me to the following problem statement: What strategy should I take to qualify for the pro-tour? But before we get into it, here’s the TLDR; if this sounds interesting, read on! If not, I just saved you 3-5 minutes, and I still got your click… everyone wins.

First, we must attempt to understand the complex system of card choices and interactions. Several new cards are now available to play from Dynasty, and there have not been large events resulting in an ‘open’ or ‘unsolved’ meta, which means there is no consensus on the best strategy, even if they are anecdotal. I start by mapping the mess and understanding the tendencies and potentials of past events to forecast an anticipated future. Historical data from the few significant events that took place since the release of the Dynasty set and games hosted online shows that there are five perceived predominant strategies or heroes in the current format. Further research on YouTube shows the most watched game influencers saying similar things.[3] This data informs my sensemaking coupled with the Cynefin model to assess that I am planning in a complex environment where a strategy of probe, sense, and respond is optimal to discover emergent practices.

Figure 1. Cynefin Model[4]

This provides the context for sensemaking and understanding complexity. This model, shown in Figure 2, uses iterations of evaluating structure, function, and process in a given context to examine assumptions and the proportions of each element in its own right, then in relationship with other members of the set. Subsequent iterations establish the validity of the assumptions and successively produce an understanding of a whole.[5]

Figure 2. use Gharajedghi’s context-function-structure-process.

Next, I look at the functions of the most popular decks. They are aggressive with a plan to gain the initiative and force their opponent to react. The deck structure is hyper-aggressive and generally lacks the resources to pivot effectively into a midgame strategy. In the more extensive process of the game, these decks are ideal in an uncertain environment because of their efficient linear gameplan, which usually gives the edge to the aggressive player in an ‘unsolved meta.’ Next, I iterate again and add the context of the current local meta I have observed. This meta is very aggressive, like the global meta. The structure of the decks is similar, and there has not been much competition against disruption strategies, mainly because the best local players are employing an aggressive strategy. I confirm my assessment that an emergent practice will best be used to probe this complex environment, observe the interactions, and respond to any counteractions. This is an iterative process, and there are four events in the next 30 days that I can iterate on with the goal of qualifying.

Next, I use superforecasting methods to create a hypothetical future operating state of a field of 24 players with insights gained through the previous mapping of the mess process.[6] Keeping with the method of superforecasting, I try to be as precise as possible when extrapolating the context I gained in researching tendencies and potentials.

Figure 1.3 Mapping the mess and Forecasting.

The center of Figure 1.1 illustrates my desired end state: qualified for the pro-tour. The next ring shows the current dominant strategies and their corresponding data. The next ring shows the positives and negatives of each strategy. The final ring represents the favored and unfavored matchups between the competing strategies, with the diamond depicting what I have observed locally. To the right of the diagram is a projected future local qualifying tournament. This data is the summation of the current global and local tendencies. Now that I understand what the field of competition looks like, I can deduce my probabilities of facing each strategy. I set out to test the hypothesis that an aggressive disruption strategy with the hero Lexi will place me in the best position to qualify for the Top 8. This is the first step in winning a tournament. However, considering the fundamentals of chaos theory’s assertion that forecasting is highly sensitive to initial conditions, I decided that predicting the Top 8 from a projected field of 24 is outside the scope of this design process. In card games, just like military planning, the enemy has a vote, and there is chance, fog, and friction standing between you and victory. This hypothesis tests what strategy gives me the highest position of relative advantage at the start of the tournament to make a run to the championship round as opposed to the concept of foresight in predicting what will win. Forecasting is probabilistic; foresight is deterministic. This card game is an open system[7]; players adapt to emerging strategies. Therefore, it would be incorrect to approach this problem with a deterministic prediction tool.

Using the projected field of 24, I deduce that the aggressive disruption strategy with the hero Lexi gives me a 65% chance of a favorable round 1 matchup. The way seeding and round robin work in this game is that the difference between a round 1 win and loss equates to a minimum of 5% chance of advancing to the Top 8 since the first tiebreaker is the round of first loss. As the tournament continues, my hypothesis continues to increase its chances of a favorable matchup with the underlying assessment that most players will be on an aggressive strategy, and winners continue to play winners in this round-robin system, so the more I win, the more likely I am to play into aggressive strategies. I will now test my hypothesis at a local qualifier; the data collected in playing and interacting with the local game meta will provide another iteration of context that will either reject my hypothesis or guide it to further modification. The tools of design have provided me with the tools to understand my operating environment, from which I have developed a “theory of victory” that will be tested in action this weekend. This skill set that design and systems thinking provides applies to the military and the business world and shows how design can drive a plan of action in a complex environment.

Part II: The Hypothesis Tested

            I tested the hypothesis that an aggressive disruption strategy with the hero Lexi would yield the greatest position of relative advantage to advance into the Top 8 to compete for pro-tour qualification. The hypothesis was not proven null and has room for further improvement. Furthermore, the tools of forecasting from Tetlock and Gardner were roughly accurate.

Figure 2.1 Hypothesis in Practice

The underrepresented variable was player skill in deck strategy. This is the new context I will use in the next iteration of context-function-structure-process. The modifications to my hypothesis are a qualitative analysis of the players executing the strategies and an exploration of an alternative strategy to exploit weaknesses in the hyperaggressive strategies. The first iteration of the hypothesis fell into a cognitive trap that plagues military analysts across time; the emphasis is on quantitative and little regard for qualitative analysis. This requires modifications to the hypothesis by providing a weighed value for player skill. This addition aims to acknowledge individual skill’s effect on executing the deck process observed in the most recent pro-tour qualifier. Finally, playing the game changes the game. The next modification will factor in the social aspect of players observing an effective counter-strategy and adapting to it, which would see an increase in Lexi disruption strategy and the most effective counter-strategy to both Lexi disruption that mimics that strategy’s ability to disrupt decks, Oldhim control, which was previously not a predominate strategy. The problem statement has now evolved to factor in these environmental changes: what strategy has the best position of relative advantage against the aggressive strategy without yielding an advantage into the Lexi and Oldhim control strategies?

Part III. Conclusions

            Time restraints and outside factors ended the testing of my hypothesis after week one; however, despite the truncated research window, there are good takeaways.

There is no such thing as a silver bullet in games or life. Hopefully, this article provides you with some resources and a basic understanding of design and systems tools that you can use to make more deliberate decisions. When you do not get the desired outcome of those decisions, you can reflect on the why or how and be better. Surprises challenge us to grow cognitively, and if we can meet surprise with acceptance and not avoidance, we can focus on a growth mindset which will improve our outlook not only in games that we play but also in life.


Bertalanffy, Ludwig von, Wolfgang Hofkirchner, and David Rousseau. General System Theory: Foundations, Development, Applications. Revised edition. New York: George Braziller Inc., 2015.

Gharajedaghi, Jamshid. Systems Thinking: Managing Chaos and Complexity: A Platform for Designing Business Architecture. 3rd edition. Morgan Kaufmann, 2011.

Tetlock, Philip E., and Dan Gardner. Superforecasting: The Art and Science of Prediction. Crown, 2015.

The Top Decks to Play for ProQuest Season 3 | FABTCG Classic Constructed, 2023.

US Department of Defense. Joint Staff. Joint Publication 5-0, Joint Operations Planning. Washington, DC: Government Printing Office, 2011. III-4.

[1] Jamshid Gharajedaghi, Systems Thinking: Managing Chaos and Complexity: A Platform for Designing Business Architecture, 3rd edition (Morgan Kaufmann, 2011), 93.

[2] Philip E. Tetlock and Dan Gardner, Superforecasting: The Art and Science of Prediction (Crown, 2015).

[3] The Top Decks to Play for ProQuest Season 3 | FABTCG Classic Constructed, 2023,


[5] Gharajedaghi, Systems Thinking, 93.

[6] Tetlock and Gardner, Superforecasting.

[7] Ludwig von Bertalanffy, Wolfgang Hofkirchner, and David Rousseau, General System Theory: Foundations, Development, Applications, Revised edition (New York: George Braziller Inc., 2015).

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